Multiple sclerosis (MS) is a chronic debilitating disorder characterized by demyelination of the central nervous system and is the second most common cause of acquired neurologic disability arising in early to mid adulthood. MS is an etiologically complex disorder with a strong but poorly understood genetic component. Four recent genomic screens each identified many potential genomic regions harboring MS genes. However, few of these regions overlapped across even two studies and none overlapped across all four. These results suggest that the genetics of MS are even more complex than previously thought. Even the major histocompatibility complex (MHC) on chromosome 6, which has been consistently associated with MS in studies of sporadic patients, was initially identified in only two of the four genomic screens (although all four have evidence upon follow-up). The MHC is likely to be the strongest genetic susceptibility in MS, yet accounts for as little as 20% and at most 50% of the overall genetic effect in MS. Although many additional biological candidate genes have been proposed and tested, the results have been inconsistent. The challenge now is to solve several problems previously inherent in these studies including small sample size, inadequate study design, and heterogeneity at both the genetic and clinical levels. To accept this challenge, we propose using a unified genetic approach to further dissect the genetic etiology of MS. We will attach the problem with a much larger sample seizure of multiplex families, an extensive dataset of MS singleton "triads", new genetic epidemiological techniques, and consider explicitly clinical and genetic heterogeneity. More specifically, we propose to: identify the probably genomic locations of susceptibility genes in MS using efficient, detailed genomic screening on a large set of multiplex families; to examine in detail these promising genomic regions; to use the transmission/disequilibrium test (TDT) to test locational candidate genes in these promising regions; to test for gene/gene interactions; and to use clinical and biological risk factor information on the families to test for genotype/phenotype correlations.